10 Things Retailers Can Do With BI

Data analytics in the retail industry is not something new. Retailers have been tapping into data for years now, gaining what is called consumer or shopper insights to improve their performance.  They have access to loads of data that comes from multiple data sources: purchase transactions, CRM data, customer loyalty programs, etc.

Now, in the age of the consumer, achieving customer satisfaction and engagement is more challenging than ever. This is an era where consumers are super informed. They want to know everything, and in real-time. They expect companies to provide solutions immediately. That’s why smart data discovery and BI tools are being used by retailers to get a much better understanding of customer behavior and preferences. In this new consumer era, smart data analytics is no longer a plus, it’s a must-have.

To justify why it’s a must-have, we’ve put together a list of 10 very cool things retailers can do with BI.

10 Things To Go From Good To Awesome

  1. Analyze transactions, customer in-store journeys and customer interaction with the product and/or brand.
  2. Thanks to self-service analytics, store managers now have access to BI dashboards that allow them to visualize and analyze the store data. They can get notifications if there are any anomalies in the data; with this they can detect problems in the supply chain, in the production process, or in the sales process. Store staff can analyze each day’s performance and can monitor KPIs in almost real-time. BI solutions help empower store managers and sales associates by delivering data analytics right to their hands. They can access dashboards and reports sent to their email through any mobile device. Plus get notified of any change in their data, KPIs, etc.
  3. Managers can analyze basket affinities, to determine which products commonly sell together. This enables them to do proper product bundling and tailor sell propositions accordingly.
  4. Some retailers also use data insights to predict product allocation during high seasons. They can predict what products to stock in which stores, during what time of the year, and how to do correct product bundling.
  5. Using data, retailers can choose which products to feature on their website’s home page. Even better, they can choose which models to show to which type of customers.
  6. Analyze transaction and other data to ensure that the right number of employees are working in a specific location at a specific time to provide the best customer service.
  7. Data analytics helps detect any issues in the production stage, inventory or supply chain. It can increase overall operational efficiency greatly. Retailers can now get a full picture and understand their data through different channels: commerce, supply chain, and customer relationship management.
  8. Retailers can use data analytics and Geo-analytics to map the performance of different stores in specific regions. This helps optimize their marketing offers in certain areas.
  9. Smart Data helps retailers anticipate demand and ensure product availability at the right location. It also enables them to do dynamic pricing and relevant, timely offers and promotions.
  10. Retailers can understand the correlation between external factors like weather, cultural trends, and competitors with their own sales. They can then detect specific issues and decide on specific actions to improve performance.

Real Examples To Inspire You

One of the biggest department stores in the USA says smart data analysis is a key competitive advantage for them and has helped boost their sales by 10%. A key player in the jewelry retail market, had a 49% increase in sales during the last holiday season and attributes a large part of this increase to the use of smart data. McKinsey did an analysis of more than 250 engagements over a five-year period. The results revealed that companies that put data at the center of the sales and marketing decisions improved their marketing ROI by 15 to 20%.

Smart BI in retail goes far beyond personalized coupons at checkout. It means a 360 degree view and understanding of the customer. It means taking data insights and turning them into specific actions that boost revenue and customer engagement and satisfaction. It means ensuring the company’s success, not just survival, in the age of the consumer. You can achieve this easily with great BI tools like Necto 16. For more information on how smart data can help a specific business, contact us at dhurtado@panorama.com . We’ll be happy to provide examples for specific scenarios.

 

 

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